Unless otherwise indicated herein, the materials described in this section are not prior art to the claims in this application and are not admitted to be prior art by inclusion in this section.
About two-thirds of all global electrical power is delivered to electric machines. It has been suggested that global electrical power consumption could be reduced by five (5) percent (%) or more through the use of power loss minimization technology.
The dominant form of an electrical machine is an alternating current (AC) induction machine, representing perhaps 90% of all energy consumption in these electric machines. Many such machines operate at loads well below their rated level, or are otherwise used in a less-than-optimum context. In emerging applications, notably electric vehicles, a motor load is highly variable and rapidly changing.
Conventional optimization techniques, which have been applied to minimize losses in AC induction machines, depend on motor parameters that are usually unknown, have limited accuracy, or are too slow to adjust for minimum power loss with time-varying loads.
Therefore, there exists a need for a method and system that can actively adjust an induction machine operation in order to minimize power losses and therefore maximize the efficiency of the induction machine in any operating conditions.